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Advection of Biomass Burning Aerosols towards the Southern Hemispheric Mid-Latitude Station of Punta Arenas as Observed with Multiwavelength Polarization Raman Lidar
In this paper, we present long-term observations of the multiwavelength Raman lidar PollyXT conducted in the framework of the DACAPO-PESO campaign. Regardless of the relatively clean atmosphere in the southern mid-latitude oceans region, we regularly observed events of long-range transported smoke, originating either from regional sources in South America or from Australia. Two case studies will be discussed, both identified as smoke events that occurred on 5 February 2019 and 11 March 2019. For the first case considered, the lofted smoke layer was located at an altitude between 1.0 and 4.2 km, and apart from the predominance of smoke particles, particle linear depolarization values indicated the presence of dust particles. Mean lidar ratio values at 355 and 532 nm were 49 ± 12 and 24 ± 18 sr respectively, while the mean particle linear depolarization was 7.6 ± 3.6% at 532 nm. The advection of smoke and dust particles above Punta Arenas affected significantly the available cloud condensation nuclei (CCN) and ice nucleating particles (INP) in the lower troposphere, and effectively triggered the ice crystal formation processes. Regarding the second case, the thin smoke layers were observed at altitudes 5.5–7.0, 9.0 and 11.0 km. The particle linear depolarization ratio at 532 nm increased rapidly with height, starting from 2% for the lowest two layers and increasing up to 9.5% for the highest layer, indicating the possible presence of non-spherical coated soot aggregates. INP activation was effectively facilitated. The long-term analysis of the one year of observations showed that tropospheric smoke advection over Punta Arenas occurred 16 times (lasting from 1 to 17 h), regularly distributed over the period and with high potential to influence cloud formation in the otherwise pristine environment of the region.
On the application and grid-size sensitivity of the urban dispersion model CAIRDIO v2.0 under real city weather conditions
There is a gap between the need for city-wide air-quality simulations considering the intra-urban variability and mircoscale dispersion features and the computational capacities that conventional urban microscale models require. This gap can be bridged by targeting model applications on the gray zone situated between the mesoscale and large-eddy scale. The urban dispersion model CAIRDIO is a new contribution to the class of computational-fluid dynamics models operating in this scale range. It uses a diffuse-obstacle boundary method to represent buildings as physical obstacles at gray-zone resolutions in the order of tens of meters. The main objective of this approach is to find an acceptable compromise between computationally inexpensive grid sizes for spatially comprehensive applications and the required accuracy in the description of building and boundary-layer effects. In this paper, CAIRDIO is applied on the simulation of black carbon and particulate matter dispersion for an entire mid-size city using a uniform horizontal grid spacing of 40gm. For model evaluation, measurements from five operational air monitoring stations representative for the urban background and high-traffic roads are used. The comparison also includes the mesoscale host simulation, which provides the boundary conditions. The measurements show a dominant influence of the mixing layer evolution at background sites, and therefore both the mesoscale and large-eddy simulation (LES) results are in good agreement with the observed air pollution levels. In contrast, at the high-traffic sites the proximity to emissions and the interactions with the building environment lead to a significantly amplified diurnal variability in pollutant concentrations. These urban road conditions can only be reasonably well represented by CAIRDIO while the meosocale simulation indiscriminately reproduces a typical urban-background profile, resulting in a large positive model bias. Remaining model discrepancies are further addressed by a grid-spacing sensitivity study using offline-nested refined domains. The results show that modeled peak concentrations within street canyons can be further improved by decreasing the horizontal grid spacing down to 10gm, but not beyond. Obviously, the default grid spacing of 40gm is too coarse to represent the specific environment within narrow street canyons. The accuracy gains from the grid refinements are still only modest compared to the remaining model error, which to a large extent can be attributed to uncertainties in the emissions. Finally, the study shows that the proposed gray-scale modeling is a promising downscaling approach for urban air-quality applications. The results, however, also show that aspects other than the actual resolution of flow patterns and numerical effects can determine the simulations at the urban microscale.